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Financial condition indices for emerging market economies: can Google help?

Author

Listed:
  • Fabrizio Ferriani

    (Bank of Italy)

  • Andrea Gazzani

    (Bank of Italy)

Abstract

We compare different approaches to constructing financial condition indices (FCIs) for major emerging market economies (EMEs). We further test whether measures of web-search intensity for keywords related to financial tensions can complement the information content of traditional financial variables. We find that an index constructed as a simple average of key financial variables augmented with data from Google searches outperforms several alternative definitions of FCIs in explaining business cycle fluctuations and capital flows episodes. These results hold true when controlling for proxies of the global financial cycle, highlighting that local financial market conditions are important for the macroeconomic performance of EMEs

Suggested Citation

  • Fabrizio Ferriani & Andrea Gazzani, 2021. "Financial condition indices for emerging market economies: can Google help?," Questioni di Economia e Finanza (Occasional Papers) 653, Bank of Italy, Economic Research and International Relations Area.
    • Handle: RePEc:bdi:opques:qef_653_21
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    More about this item

    Keywords

    financial condition index; emerging markets; Google search; principal component analysis; VAR; quantile regressions;
    All these keywords.

    JEL classification:

    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • E44 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Financial Markets and the Macroeconomy
    • F30 - International Economics - - International Finance - - - General
    • G01 - Financial Economics - - General - - - Financial Crises
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets

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